1. Field of the Invention
The present invention relates to an image correction technology, and in particular to a self-adaptive image edge correction device and method thereof, that is capable of improving the edge blurring and edge saw-tooth phenomena of an image.
2. The Prior Arts
In monitoring an image at a long distance, the image has to be enlarged to be viewed clearly. Also, to obtain an image of high resolution for that image originally of low resolution, in general, polynomial interpolation is utilized to magnify and enlarge the image. However, the magnified image could produce blurring and saw-tooth phenomena, thus leading to distortion. In this respect, the main reason for blurring is that, the effect of interpolation is equivalent to filtering out the high frequency portion of an image using a low-pass filter, hereby causing image blurring. In addition, the edge of the enlarged image could develop irregularities caused by the dislocations during interpolation, to produce saw-tooth of edges. For the reasons mentioned above, image edge blurring and saw-tooth are produced during polynomial interpolation.
To improve the shortcomings of the prior art mentioned above, two approaches are utilized to eliminate this phenomenon for the digital photos. Wherein, one approach is to increase the resolution to the extent that blurring and saw-tooth can not be discerned by the human eyes, but this could inevitably lead to increased cost. The other approach is to use a bi-linear interpolation in cooperation with a blurring filter. Yet, this could consume too much time, dire to its complicated computation process.
Moreover, to improve the edge saw-tooth phenomenon, the following approaches can be utilized: Low-Pass Filter, Error-Amended Sharp Edge, Linear Minimum Mean Square-Error Estimation, Fast Edge-Oriented Interpolation, or Grey Polynomial Interpolation. Yet, the utilization of the Low-Pass Filter could cause distortion of the entire image; the application of the Error-Amended Sharp Edge or Linear Minimum Mean Square-Error Estimation could lead to overly large computation amount, and overly long computation time; while the use of Fast Edge-Oriented Interpolation, or Grey Polynomial Interpolation requires repeated tests of threshold values, that is rather time consuming.
Therefore, presently, the design and performance of image interpolation is not quite satisfactory, and it has much room for improvements.